Uber’s self-driving cars are impressive — but there’s still a lot they can’t do

Last week, Uber rolled out its self-driving cars in a pilot program in Pittsburgh so that select users could experience the technology firsthand. But anyone who gets permission to do so will notice there’s still a driver behind the wheel.

That’s because Uber’s self-driving cars are nowhere near fully autonomous. Uber knows that, which is why there’s an engineer in the front seat overseeing the car’s movements and a safety driver behind the wheel.

I got a chance to go behind the wheel, and the Uber cars are really good at maneuvering around a tricky city like Pittsburgh. The braking was smooth, the response time was quick, and it handled intersections just fine.

But there were a few times a driver had to take over. Here are the scenarios Uber’s self-driving cars still have difficulty handling.

A big problem for self-driving cars is simply having to deal with other human drivers on the road.

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Business Insider/Corey Protin

Tech companies and automakers investing in autonomous technology are banking on an eventual future where roads are entirely composed of driverless vehicles, thereby reducing congestion, traffic, and most importantly, accidents.

But making that vision a reality will be a gradual process, and in the meantime, self-driving cars have to handle the chaotic nature of human driving. When I was in the backseat of the self-driving Uber, our driver had to take over when a truck was making a right-hand turn from a left lane, as you can see above.

It makes sense that a robotic car may not understand how to handle that situation because, by the very rules of the road, it defies all logic. But humans are messy, complicated drivers, and self-driving cars need to react quickly. It’s why several companies are turning to a branch of artificial intelligence called deep learning so cars can recognize potential hazards and react quicker.

Ironically, Uber’s self-driving cars have trouble with bridges, despite operating in a city filled with them.

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Business Insider/Corey Protin

Our driver had to take manual control of the car when going over a bridge in Pittsburgh, but it wasn’t really clear if that had to do with the bridge or simply the amount of activity happening around the car at the time.

Either way, Uber has spoken openly about the bridge problem. Raffi Krikorian, Uber’s engineering director, told Bloomberg that “bridges are really hard” because they don’t have many environmental cues, like surrounding buildings, so it’s hard for the Uber car to figure out where it is.

But that’s actually one of many reasons Uber chose Pittsburgh. Krikorian said at a press event that “Pittsburgh is the double black diamond of driving” and that’s what will allow the cars to advance.

Uber has also said extreme weather poses issues for the cars.

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AP/Alvaro Barrientos

That’s not a problem exclusive to Uber, either. Snow poses issues for driverless tech like Tesla’s Autopilot because it covers lane markings, making it hard for the car to find the lane and navigate properly.

Ford is also making an effort to test in snowy conditions and in pitch black to grapple with extreme weather as well.

It also goes without saying that weather like snow can cover sensors, making it hard for the cars to detect objects. That’s why self-driving cars have a lot of redundant sensors and cameras to make sure they can still operate safely even if some fail.

And believe it or not, even plants confuse Uber’s self-driving cars.

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Business Insider/Corey Protin

Uber told us that vegetation (yes, plants) has posed issues for the cars. That’s because self-driving cars rely on maps of their surroundings to determine where they are. Basically, the car compares landmarks to the high-definition maps to position themselves accordingly.

This is also why Uber’s self-driving cars can only drive in select parts of Pittsburgh, because not all of Pittsburgh’s routes are mapped.

When Uber first started mapping routes in Pittsburgh, it did so in the winter when there were no leaves on the trees. That confused the car when it started driving in spring, because suddenly those landmarks looked a lot different from the map version.

Lastly, obstacles that “disappear” suddenly are confusing for the cars.

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Reuters/Ralph Orlowski

At Uber’s press event for its self-driving pilot in Pittsburgh, Krikorian noted how even once an obstacle is removed, the car may still be unsure how to respond.

“We’re really tackling the long-tail of driving, things like ducks crossing in front of the car as it rolls down the road,” he said.

Basically, a regular human driver knows to wait for the ducks to cross and then proceed once they are out of the way. But with self-driving cars, it’s one them to train them to recognize a duck, it’s another to train them that they should recognize the duck, wait for them to cross, and then proceed at a certain point.

“This is still early days for us,” Krikorian said. “We’re learning every single day we’re out there on the road.”